Multiple Edge Effects and Their Implications in Fragmented Landscapes Author(S): Robert J

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Multiple Edge Effects and Their Implications in Fragmented Landscapes Author(s): Robert J. Fletcher Jr. Reviewed work(s): Source: Journal of Animal Ecology, Vol. 74, No. 2 (Mar., 2005), pp. 342-352 Published by: British Ecological Society Stable URL: http://www.jstor.org/stable/3505623 . Accessed: 07/03/2012 14:05

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http://www.jstor.org Journalof Animal Ecology2005 Multipleedge effects andtheir implications in fragmented 74, 342-352 landscapes

ROBERT J. FLETCHER JR Departmentof NaturalResource Ecology and Management, Science Hall II, IowaState University,Ames, IA 50011, USA

Summary 1. Habitat edges are thought to explain much of the negative effects arising from habitat fragmentation; however, progress has been limited in extrapolating edge effects to different situations because ecologists still do not understand if and how multiple edges interact within fragments. It also remains controversial whether edge effects govern patch-size effects, such as area sensitivity, observed in many migratory songbirds. 2. I examined how multiple edges within fragments may intensify edge responses by investigating spatial distributions of an area-sensitivesongbird that breeds in temperate grasslands of North America, the bobolink (Dolichonyx oryzivorusLinnaeus). I tested whetherbobolinks avoid edges and whetheravoidance is strongernear two edges (double- edge plots) than near only one edge (single-edge plots). I subsequently linked bobolink distributions to landscape maps that vary in the amount of habitat and degree of fragmentationto exploresome potentialimplications of multipleedges on patch-and landscape- level distributions. 3. Multiple edges appeared to influence the magnitude of observed edge effects, in which the probability of bobolink occurrence was four times lower in double-edge plots and two times lower in single-edge plots than in the interior of grasslands.Within single- edge plots, the probability of occurrence increased with increasing distance from edge. Within double-edge plots, the probability of occurrence increased as a function of the nearest and next-nearest distances from edges. Multiple edges also appeared to increase the extent of edge effects, or distance of edge influence, which was estimated to be approximately 11-33% greater in double-edge plots than in single-edge plots, depending on the next-nearest distance from edge. 4. Extrapolating local bird distributions to landscape models suggests that edge effects can have strong influences on large-scale distributions and that models incorporating multiple edge effects are different to simple nearest-edge models only in highly fragmented landscapes, regardlessof landscape composition. Furthermore,edge effects can lead to patch-size effects similar to empirical patterns of area sensitivity observed in this species. I conclude that edge effects can be intensified when multiple edges collide, a feature that permeates many fragmented landscapes. Key-words: bobolink, Dolichonyxoryzivorus, edge effect, habitatedge, patch-sizeeffects.

Journal of Animal Ecology (2005) 74, 342-352 doi: 10.111 l/j.1365-2656.2005.00930.x

isolation and increased of habitat in Introduction proportion edge landscapes. Habitat edges can influence a variety of Habitatloss generallyleads to increasedhabitat frag- population and community processes, from dispersal mentation, resulting in smaller patches, increased rates to species interactions (Paton 1994; Cadenasso & Pickett 2001), and edges are considered primary driv- ers for the Correspondence:Robert J. Fletcher Jr, Avian Science Center, effects of habitat fragmentation (Harrison & Divisionof BiologicalSciences, University of Montana,Mis- Bruna 1999). However, progress has been limited when ? 2005 British soula,MT 59812, USA. Tel: (406) 243 2035; Fax: (406) 243 4184; extrapolating edge responses to different situations EcologicalSociety E-mail:[email protected] because of many poorly understood factors that 343 potentiallymediate edge effects,including if and how that vary in the amountof habitatand the degreeof Multiple edge multipleedges interactwithin fragments(Ries et al. fragmentationto explore some potential impacts of effects 2004).This is unfortunate,because as fragmentation multipleedges on distributionsin fragmentedland- increases,patch geometry tends to becomemore complex, scapes. Extrapolatingempirical data to landscapes resultingin manyareas near multiple edges. providesa contextto determinewhether incorporating Most empiricalresearch (e.g. Chen, Franklin & Spies multipleedges into modelschanges model predictions, 1995;Brand & George2001) and models (e.g. Laurance whenmultiple edges might be importantat largescales, & Yensen1991; Sisk, Haddad & Ehrlich1997) on edges and can be useful for conservationand management haveignored multiple edge effects, which I defineas the strategies,particularly in landscapesundergoing rapid cumulativeedge effectoccurring from more than one change(Malcolm 2001; Sisk, Noon & Hampton2002). habitatedge withina fragment(sensu Zheng & Chen 2000). The nature of multiple edge effects remains Methods unknownin naturalsystems, yet multipleedges could influencenot only the magnitudebut also the extentof STUDY AREA edge effects(i.e. the distance/depthof edge influence, DEI; Harper& MacDonald 2001). Untanglinghow I surveyedbreeding birds in 10 grasslandsites (two to multiple edges influenceedge effects is particularly threeplots per site;n = 25 plots; see below)scattered importantwhen extrapolating edge effectsto different throughout northern Iowa, USA during 2001-02 patches and landscapes (Laurance& Yensen 1991; (Fig. 1). Withinthis region,I selectedall sitesthat met Malcolm2001), and it willbe criticalfor determining if the followingcriteria: (1) sites were largeenough to edge effects operateat large spatialscales (Laurance contain two 150 x 150 m plots (see below); (2) sites 2000). In fact, a recentsynthesis on edge effectssug- contained grasslandhabitat that borderedrowcrop gestedthat multipleedge effectswere a primaryissue agricultureedges (either corn or soybeans);(3) poten- limitingextrapolation of edgeresponses and identified tial plot locationsdid not includeany woody vegeta- no empirical data on how multiple edges influence tion or wetlands;and (4) grasslandsincluded restored animals(Ries et al. 2004). grasslandsor native tallgrassprairies under state or In practice,most research has focusedon the nearest federalmanagement. I surveyed birds on the sameplots distance from an edge to describeedge effects (e.g. eachyear; however, one plot was not surveyedin 2002 Lauranceet al. 1998; Harper& MacDonald 2001), because managementactivities caused this plot to eventhough complex geometry permeates many land- be unsuitablefor bobolinks.Restored grasslands con- scapes.A critical frameworkfor evaluatingmultiple tainedwarm-season and cool-seasongrass plantings, edge effectsthus requirescomparing predictions from with commonspecies including switchgrass (Panicumrn nearest-distancemodels to models using multiple- virgatumL.), big bluestem (AndropogongerardiiVitman) distancemeasures. Models that have been proposed for and smooth brome (Bromusinermis Leyss.). Prairies addressingmultiple edge effects generallygenerate containeda high diversityof nativegrasses and forbs, strongeredge effects than nearest-distancemodels includingbig bluestem,little bluestem (Schizachyrium (cf. Malcolm 1994, 1998, 2001;Zheng & Chen 2000; scopariumNash), Indian grass (Sorghastrumnutans (L.) Ferntndezet al. 2002;Fletcher 2003), and deviations Nash),switchgrass, goldenrod (Solidago spp.), sunflower of nearest-distancemodels from multiple-edge models (Helianthusspp.)andmilkweed(Asclepiasspp.).Bobolinks tendto be greaterin smallpatches or in highlyfragmented occur at similardensities in restoredgrasslands and landscapes(Malcolm 2001; Fletcher 2003). Although tallgrassprairies in theregion (Fletcher & Koford2002). fewempirical data exist regarding multiple edge effects (Ries et al. 2004),Malcolm (1994) found that an addi- BIRD SURVEYS tiveedge model explained habitat structure in Amazo- nian fragmentsbetter than a nearest-distancemodel. In 2001,within each site I establishedtwo plots (150 x I investigatedsome potentialimplications of mul- 150m; Fig. 1):one nearonly a singleedge (single-edge tipleedges on distributionsof a migratorysongbird that plots hereafter),and one neartwo edges,or a comrnerof breedsin grasslandsof the UnitedStates, the bobolink the site (double-edgeplots hereafter).Elsewhere we (Dolichonyx oryzivorus Linnaeus). Bobolinks have documentedthat averageterritory sizes of malebobo- experiencedpopulation declines (Peterjohn & Sauer links near agricultureedges were ha ha; 0.34 (+ 0.05 1999;Fletcher & Koford2003b) and havebeen docu- Fletcher& Koford2003a); therefore, within each plot mentedto be sensitiveto habitatfragmentation, by both approximatelysix to sevenmales could occur if plots avoidingedges (Fletcher& Koford2003a) and being weresaturated. Both plots withinsites containedsim- area-sensitive,or less likely to occur in small patches ilar vegetationtypes (prairieor restored;cool-season Johnson & 2005British (Herkert 1994; Igl 2001). Therefore, I or warm-seasongrasses) and werelocated near linear ? thatbobolinks would be less to occurin EcologicalSociety, expected likely rowcropagriculture edges. Each plot was placed at Journalof Animal areasnear multiple edges more so than in areasnear least 150m fromany otheredge (otherthan the edges Ecology, 74, only one edge. I tested this and subsequentlylinked of interest)in the site to minimizeeffects from other 342-352 bobolink occurrence data with landscape maps edges. This bufferdistance was based on Fletcher& 344 (a) Study area and 125 m from the edge. Before each survey, the R. J. Fletcher observer picked the order and direction randomly to surveytransects. During each survey,the observerwalked transects at a steady pace, recording all birds seen within 25 m of the transect. Care was taken not to count the same bird more than once. When collecting data, observations were divided into 25 x 25 m cells within the plots. Although individuals probably used more O Studysites than one cell, these cells allow for high resolution in the near and the i I Samplingregion interpreting spatial patterns edges, analysis accounted for this potential lack of independ- (b) Single-edgeplots ence (see below). For double-edge plots, this enabled each cell to be described by two measures for distance from edge: a nearest distance (d,,,) and a next-nearest distance (d,,,,d).Surveys were conducted between sunrise and 4 h after sunrise, when breeding birds are most i i ? i ; active. Surveys were repeated four times during the breeding season, from 20 May until 6 July, 2001-02. N rest : Each year three observers conducted surveys and each .... distance, nd site was surveyed by each observer at least once. In 2002, I added interior plots at five of the 10 sites. Interior plots consisted of transects that were 100 x 50 m. Each interior plot was placed at least 200 m from any edge within the site. Interiorplots weresampled using the same protocol as single- and double-edge plots. 25 75 125

The study design allows for two levels of resolution for determining if multiple edges influence bird distribu- 125 tion. First, at the plot level, I tested for differences in male bobolink occurrence in single-edge, double-edge and interior plots. Secondly, I tested whether the dis- o 75 ext-neare tance to the nearest edge and next-nearest edge could O0 explain male bobolink occurrence within plots. I ran three separate analyses: one at the plot-level, testing for UrNearest o differences in occurrence among plots, and two analy- distance,n,d 25 - ses within plot types, testing for effects of distance to the nearest edge and next-nearest edge in explaining occurrence.I evaluatedoccurrence using logisticregression 25 75 125 models, adjusted for spatial correlation within plots Distance from edge (m) (Littell et al. 1996). Site was considered a block (and random effect), and year was considered a split-plot Fig. 1. Study sites (n = 10)and surveydesign used for estimating the influenceof multipleedges on bobolinkdistribution, northern repeated measure to accommodate non-independence Iowa, 20014-02.(a) All sites meeting samplingcriteria (managed between years (Littell et al. 1996: 88-92). For distance grassland patches bordering rowcrop agriculture that could effects within plots, I tested whether slopes (on the logit contain a single-edge and double-edge plots) within the dashed scale) were zero by using the midpoint distance of each region were sampled. In each site, there were paired survey grid cell from the edge m, m, 62-5 m, etc.) as plots (150 x 150 m): (a) single-edgeand (b) double-edge(corner) (12.5 37.5 plots. Observations were grouped into 25 x 25 m grid cells, a continuous variable. This design controls for patch- which allowed for nearest distance and next-nearest distance level covariates, such as patch size and landscape measures in double-edge plots. In 2002, interior plots, located context, by considering site as a block in the sampling > 200 m from any edge, were added to half of the study sites. design. None the less, I initially explored potential patch-size effects by including patch size as a covariate Koford (2003a), which suggested that edge effects on in analyses;however, there was no evidence of patch size bobolink abundance occur within approximately influencing edge responses in any analysis (P > ? 2005 British 0.20), 75-100 m from edges. Each plot contained three fixed- so I removed it from final models. Within-season Ecological Society, a if a Journal of Animal width line transects running parallel to the edge in sampling was pooled by considering cell occupied Ecology, 74, single-edge plots, and parallel to a randomly selected male bobolink was observed in the cell during at least 342-352 edge on the double-edge plots, at distances of 25 m, 75 m one visit. Elsewherewe have estimated high detectability 345 of male bobolinks up to 50 m from observers (Fletcher 1998; Harper & MacDonald 2001). I approximated the Multiple edge & Koford 2002). DEI as the distance in which the interior lower con- effects Accounting for spatial correlation is a critical issue fidence limit overlapped with the models (means and for appropriate inference regarding edge effects as well confidence limits) within each plot type. These approx- as other ecological processes (Brand & George 2001; imations are not intended to provide an absolute esti- Keitt et al. 2002). Because observations in adjacent mate of the extent of edge effects, but they are useful for cells were not independent,I adjustedmodels for within- comparative purposes between the two plot types. plot spatial covariance by estimating the nugget, partial sill and range parameters of the semivariogram LANDSCAPE EDGE MODEL explaining spatial correlation within plots (Littell et al. 1996: 303-330). Moreover, using distance as a con- To explore some potential implications of edge effects tinuous explanatory variable minimizes problems of on bird distributions, I used a simulation model that potential pseudoreplication within plots because cells linked empirical data on bobolink distributions with are used only in estimating a slope parameter for each fragmentedlandscape maps. I used two types of landscape plot (i.e. the plot is the effective unit of replication; maps: (1) theoretical maps that allowed for exploring Fletcher & Koford 2003a). I considered six isotropic differentlevels of habitatloss and fragmentation(neutral (i.e. correlation independent of direction; Gaussian, landscapes; Gardner 1999) and (2) real maps of inde- exponential, linear, linear log, power and spherical; pendent areas in northern Iowa, centred geographi- Littell et al. 1996: 305) and two anisotropic models (i.e. cally on the survey area. Each map was a 256 x 256 grid correlation dependent on direction; anisotropic expon- of cells (25 x 25 m) that contained suitable habitat ential and power; SAS Institute 2001) for explaining and unsuitable matrix, which allowed the appropriate covariance structure and compared these models to an extrapolationof empiricaldata to landscapemaps. There- independent errors model that did not adjust for spa- fore,landscape size was x km (41 km' or 4096 ha). 6.4 6.4 tial covariance. Models were compared using Akaike's Patches were delineated using a nearest-neighbour rule, informationcriterion, adjusted for sample size (Burnham in which patches were defined based on contiguous & Anderson 1998). orthogonal clusters of cells (Gardner 1999). I also approximated the distance of edge influence I generated theoretical landscapes that varied in the and determined if this distance changed near multiple amount of habitat and degree of fragmentation using edges. I overlappedinterior estimates of occurrencewith the program RULE(Gardner 1999). Maps were gener- estimates derived as a function of distance from each ated with 10%, 30% and 50% suitable habitat in the edge within single-and double-edgeplots (Lauranceet al. landscape (Fig. 2). Fragmentation was varied by using

Fragmentation

50% 3

30% 2

10%__

H= H= H= SR 1.0 0.5 0.0 Iowa Theoreticallandscapes Real landscapes Fig. 2. An example of real and neutrallandscapes used in linkingmultiple edge effectsbased on bobolinkdistributions to fragmented landscapes. Suitable habitat is denoted in white, unsuitable matrix is in black. For theoretical landscapes, both simple (C 2005 British random and fractal landscapes were generated using program RULE(Gardner 1999). Fragmentation was varied by changing H, Ecological Society, the spatial contagion of the fractal landscape, and comparing these fractal landscapes with simple random (SR) landscapes. For Jourinalof Animal each landscape type, 10 landscapes were generated and used in simulation modelling. For real landscapes, I used three simplified Ecology, 74, maps of areas within the Eagle Lake Wetland Complex, northern Iowa. To do so, I considered all grassland habitats as potentially 342 352 suitable habitats, except for narrow (< 6 m) roadside ditch areas, and all other habitats as unsuitable matrix. 346 both simplerandom maps (SR) and fractalmaps for multipleedge effect process(Malcolm 1994, 2001), I R. Fletcher eachamount of habitat.For simple random maps, each did not use modelsthat incorporateddistances to all J. cell in the landscapehas an independentprobability of edges becauseempirical data only directlyaddressed beingsuitable habitat, conditional on thetotal amount effectsfrom < 2 edges. of habitat in the landscape. For generatingfractal I simulateddistributions in landscapesfor each maps,RULE uses the midpointdisplacement algorithm, model type by assumingthat occurrencewithin each in which spatial contagion (or clumping) is varied habitatcell was a Bernoulliprocess, in whicha cell was basedon a parameter,H, that rangesbetween 0 and 1 occupiedwith a probabilitytaken from estimates of the (Gardner1999). Maps were generatedwith H = 0-0, logistic models.The null model used the probability and When H = are more estimatefrom interior Thenearest-distance model 0.5 1.0. 1.0 landscapes plots. clumped (and thus less fragmented);when H = usedprobability estimates from single-edge plots when 0"0 landscapesare highlyfragmented, and SR landscapes dd < 150 and the interior estimate when dd > 150 m; arean extremeform of fragmentation(Fig. 2). Twelve thismodel is similarto previousmodels on edgeeffects landscapetypes were generated, with 10landscapes for (Sisk et al. 1997). The next-nearest-distancemodel each type. used probabilityestimates from double-edge plots In additionto theoretical I used three when and < 150 estimateswhen maps, simpli- dnd dnnd m, single-edge fied maps of real landscapeswithin the Eagle Lake dd < 150 and d,,d 2 150 m and interior estimates when WetlandComplex, a 162-km2area targeted for conser- dd and d,,d 2 150 m. From these simulations I vation and restorationstrategies focused on breeding addressedthe following:(1) do differentmodel types birdsin north-centralIowa (43?N,94?W; Fletcher & predict differentpatch- and landscape-levelrelative Koford2002, 2003b).To do so, I consideredall grass- densities,and (2) do these predictionsvary with the land habitats(e.g. pastures,hayfields, restored grass- amountof habitatand degree of fragmentation?For all lands) as potentially suitable habitats (Fletcher & models I focused on predictedfrequencies of occur- Koford 2003b), except for narrow(< 6 m) roadside rencefor comparisons. However, these models can also ditchareas (Camp & Best 1993)and all otherhabitats be comparedusing predicted total populationsizes by as unsuitablematrix (Fig. 2). High resolution(2-3 m) multiplyingthe amountof suitablehabitat by the pre- vectormaps wereconverted to rastermaps with 25 x dictedfrequencies of occurrence.Focusing on thetotal 25 m cellsto linkempirical data appropriately with the populationsize did not changepatterns qualitatively, Iowamaps. Landscapes were the samesize as theoret- exceptthat landscapes with more habitat were predicted ical landscapesand did not includeany sites thatwere to harbourlarger populations of bobolinks,regardless used for birdsurveys. While these maps provide more of the modeltype used(null, nearest distance, or next- realisticland use scenariosthan theoreticalmaps, I nearestdistance; R. J.Fletcher, unpublished analysis). emphasizethat many issues arise when extrapolating to real et al. and elsewherewe landscapes(Wiens 1993), Results havedocumented that male bobolinksrespond differ- ently in both behaviourand abundanceto different BOBOLINK DISTRIBUTIONS edge types (Fletcher& Koford2003a). None the less, because male bobolinks respond less to agriculture In 2001,my assistantsand I recorded207 observations than other at local scales & of bobolinks transects males;n edges edge types (Fletcher along (61.8% = 128), Koford these models con- and in 2002 we recorded249 observations 2003a), probablyprovide (61.0% servativepatterns for the negativeeffects of edges on males;n = 152).In bothyears, bobolinks were the most bobolinkdistributions. commonbird observed on transects.Overall, the prob- Edgeeffects were modelled using a similarapproach abilityof occurrencefor male bobolinkswas greatest to the EffectiveArea Model developedby Sisk et al. on interior plots and least on double-edge plots (1997),but I usedthe probability of occurrence(derived = P = Fig. 3a), with mean estimates (F2,3 8.34, 0.0047; fromlogistic models) for modellingand incorporated of occurrencebeing four times loweron double-edge multiple edges into the modelling process.For each plots and two timeslower on single-edgeplots thanon habitatcell in the landscape,distances from each edge interiorplots. In single-edgeplots, the probabilityof were calculatedin each cardinaldirection. Distances occurrenceincreased as a functionof distancefrom werethen used to estimatethe probability of occurrence edge (Table1, Fig. 3b), and I estimatedthe DEI to be basedon threetypes of modelsderived from empirical approximately88 m, based on predictedprobabilities data:(1) a null model,in whichno edge effectoccurs; of the logistic model within plots (60-116 m using (2) a nearest-distancemodel, in which information upperand lowerconfidence limits of predictedvalues, fromonly the nearestedge was usedto estimateoccur- respectively).In double-edgeplots, the probabilityof rence;and a next-nearest-distancemodel, in which occurrenceincreased as a functionof the nearest(dd) 2005British (3) ? both the nearestand next-nearest wereused in and next-nearestdistances 1, EcologicalSociety, edges (dnnd)from edges (Table Journalof Animal estimatingoccurrence. While some approachesallow Fig. 3c). In double-edgeplots, the estimated DEI Ecology, 74, for extrapolatingbeyond the numberof edgesinvesti- rangedfrom approximately 98 m to 117m, depending 342-352 gatedempirically, given certain assumptions about the the next-nearestdistance from edge (27-91 m and 347 U) Table1. Summaryof logistic regressionmodels describing o 0"5 (a) Multiple edge U) malebobolink occurrence near one edge(single edge) or near 0-4 two edges(double edge) in northernIowa, 2001-02. Sitewas efJfects 0 0-3 considereda randomeffect and yearwas considereda split- o plot repeatedmeasure. Models were adjusted for spatial 0.2 covariancewithin plots by estimatingthe semivariogram

o.D explainingspatial correlation within plots. For both single- ..,-, 021 0 and double-edge analyses, the best structure (based on Akaike'sinformation criterion, adjusted for samplesize) for these wasa covariancestructure 0"0 Double Single Interior estimating parameters power [Oii= c2(pdi')] a> 0.5 / o (b) Parameter d.f. F P

0.4 o 0.a Singleedge 0-2 Nearestdistance 1, 9 37-08 < 0.001 Year 1, 662 2-65 0.104 Yearx nearestdistance 1, 662 0 137 o 0-10 .. 2.22 . n 0* Doubleedge 0? - 01_0-2 //'- Nearestdistance 1, 9 14.49 0.004 0 25 50 75 100 125 150 Interior Next-nearestdistance 1, 9 5.74 0-040 Year 1,687 1-60 Distancefrom edge (m) 0.206 Yearx nearestdistance 1, 687 0.35 0.552 Yearx next-nearestdistance 1, 687 0 105 2.63 0e5 /--7

0-4 proportion of habitat within 50 m of each edge was "o 0. 11- high for all patch sizes in highly fragmented landscapes (SR, H = but in less fragmented landscapes (H = .0 02013 0"0), 0-5, 1-0) the proportion of habitat near edges declined .• 0-1 precipitously as a function of patch size (see Fletcher 0150 7 2003). The Iowa landscapes considered contained little Dtn ~ o edg 150 C~ suitablehabitat (< 17%/),had generallysmaller maximum ( Distance25••0_. patch sizes than theoretical landscapes (except for SR from and suitable habitat was closer to edge (r) 0\ landscapes) edges compared to most fractal landscapes (Table 2). For the Fig. 3. Theestimated probability of occurrence(per grid cell considered, the of habitat near withinplots; based on logisticregression analyses) for male landscapes proportion bobolinksin double-edge,single-edge, and interiorplots in the nearestand next-nearestedges was much greaterthan northernIowa, 2001-02. (a) The probabilityof occurrence near the other edges, suggesting that the distances to SE) percell as a functionof plot type,(b) the probability the two closest edges capture most variation in edge- (S. of occurrence (. + 95% CL) as a function of distance from related spatial characteristics of habitat (Table 2). edgein single-edgeplots and (c) the probabilityof occurrence At the patch level, the predicted frequencies of (i• 95%CL) based on both nearest(d,,,) and next-nearest distances(d,,,,1) from edges in double-edgeplots. Note that occurrence (mean number of individuals/cell) from each combinationof d,,, and d,,,doccurs in two cells within next-nearest distance models were lower than nearest plots (except when d,, = d,,,,,),given the symmetric nature of distance models for all patch sizes in the most frag- double-edgeplots. The intersection of thelower confidence limit mented landscapes (SR, H = Fig. 4). In less frag- of theinterior estimate (dashed line in b andc) andthe predicted 0.0; mented landscapes, next-nearest distance models valuewithin single- and double-edgeplots approximatesthe lower of occurrence for DEI (sensuLaurance et al. 1998). predicted slightly frequencies patch sizes approximately < 50 ha. Only in very large patches (> 150 ha) did predictions from edge-effect > 150 m using upper and lower confidence limits of models approach predictions from null models (Fig. 4). predicted values, respectively). Overall, there was no Iowa landscapes exhibited similar patterns to neutral evidence for year effects or interactions of edge and landscapes (Fig. 4). year effects (Table 1). At the landscape level, predicted frequencies of occurrence based on next-nearest distance models were lower than nearest-distance models only in the most LANDSCAPE MODELS fragmented landscapes, but this occurred regardless Physical characteristics of theoretical landscapes var- of the amount of habitat in the landscape (Fig. 5). ? 2005 British ied in predictable ways (Table 2). The proportion of With less fragmented landscapes, edge effects were Ecological Society, habitat within 50 m of the nearest and the next-nearest Journal of Animal still important, with edge models predicting lower fre- Ecology, 74, edge was much greater in highly fragmented land- quencies of occurrence than the null model, but simple 342-352 scapes (SR, H = 0-0; Table 2). At the patch level the nearest-distancemodels were comparableto next-nearest 348 Table 2. Some physical characteristics of theoretical landscapes (generated by program RULE;Gardner 1999) and Iowa R. Fletcher landscapes used in linking multiple edge effects to fragmented landscapes . Percentage Mean Patch size Proportion near edgesl suitable no. of Landscape typet habitat patches Mean Maximum Edge 1 Edge 2 Edge 3 Edge 4

Theoretical SR 10 1-00 0-96 4703.6 0.1 0.6 1.00 1.00 SR 30 1-00 SR 50 7551.5 0.2 2.9 1.00 0.96 0.69 3906.0 0.5 30.7 1.00 0.95 0.74 0.32 H= 0-0 10 0-85 0-41 1621.8 0.2 81.5 0.96 0.68 H= 00 30 0-5 0-67 2226.5 311.3 0.86 0.45 0.21 H=0-0 50 0-48 0-27 0-11 1681.9 1.1 1400.1 0.72 H=- 0-5 10 220-4 1-5 347-4 0-32 0.51 0.17 0.06 H=- 0-5 30 379-5 0-18 2.9 1046.3 0.32 0.09 0.03 H= 50 4-7 0-13 H= 0.51-0 10 396.7 1957.8 0.24 0.06 0.02 10.8 29.8 411.8 0.15 0.07 0.01 0.00 H= 10 30 0-09 0-04 0-01 28.3 36.6 1136-6 0.00 H = 1-0 50 0.01 0-00 21.4 84.2 2042-8 0.06 0.03 Real Iowa 1 3 0-42 0-03 28.0 9.5 21.9 0.82 0.15 Iowa 2 11 116-7 200-3 Iowa 3 17 30.0 0.54 0.17 0.03 0.00 109.0 110.1 236.0 0.60 0.25 0.07 0.01

tSR = simple random (most fragmented); and 1-0 refer to the spatial contagion (or clumping) parameter, H, of the landscape, in which is the least clumped,0.0, or most0"5, fragmented, and is the most clumped, or least fragmented (Fig. 2). Ten 0.0 1.0 landscapes were generated for each neutral landscape type (n = 120 landscapes). For real landscapes, numbers refer to maps shown in Fig. 2. SProportion of suitable habitat located within 50 m from an edge. Edge 1 refers to the distance to the nearest edge, edge 2 refers to the distance to the next-nearest edge, and so on.

distance models (Fig. 5). Similar patterns occurred in a local scale bobolinks are more sensitive to woodland Iowa landscapes, with simple nearest-distance models edges than agricultureedges (Fletcher & Koford 2003a), predicting only slightly higher frequencies of occur- but woodland edges occupy much less area in Iowa rence than next-nearest distance models. landscapes. At a landscape scale bobolinks are more sensitive to density of agriculture edge than woodland Discussion edge (Fletcher & Koford 2002), which is probably the result of the prevalence of agricultureand multiple edge effects occurring within these highly fragmented MULTIPLE EDGE EFFECTS AND BIRD landscapes. DISTRIBUTIONS Although edges affected bobolink distributions, Edge effects can be intensified when multiple edges untangling the processes that underlie these patterns converge and these effects could have strong impacts will improve our understanding of multiple edge on bird distributions in highly fragmented landscapes. effects. Some potential mechanisms for edges influenc- I documented that multiple edges increased both the ing bird distributions include changes in habitat struc- magnitude and extent of the edge effect on bobolink ture, food availability and species interactions near distributions. While my results were confined to a sin- edges (Fletcher & Koford 2003a; Ries et al. 2004), gle bird species, multiple edge effects probably operate some of which could potentially be exacerbated near on any species influenced by habitat edges (Fletcher multiple edges. For example, bobolinks are known to 2003). Harrison & Bruna (1999) suggested recently that have high site fidelity in areas with high reproductive most effects arising from habitat fragmentation were success (Bollinger & Gavin 1989). If nesting success is driven by edge effects. Thus, understanding the effects generally lower near edges due to increased predation of habitat fragmentation will require understanding risk (Johnson & Temple 1990; Paton 1994), then edge effects,which will ultimatelyrequire understanding bobolinks may have lower site fidelity near edges than how multiple edges influence edge responses. Coupled in the interior of grasslands. In a similar area of Iowa, with other important factors, such as the type of edge Kuehl & Clark (2002) found that predator activity was (Fletcher & Koford 2003a) and landscape structure greater near the corners of fields than along single (Bakker,Naugle & Higgins 2002), multiple edge effects edges, which they attributed to predators using corners ? 2005 British might help explain regional variation of fragmentation for and This activ- EcologicalSociety, entering exiting grasslands. greater Journalof Animal sensitivity within species (Johnson & Igl 2001). The ity could reduce nesting success further near multiple Ecology, 74, relative importance of these factors probably varies edges. Elsewhere we have documented that habitat 342-352 depending on the scale of investigation. For instance, at structuredoes not change near these and other edges in 349 o Null 0 Nearest Distance * Next-nearest distance

Multiple edge (a) Theoreticallandscapes effects 10% Habitat 30% Habitat 50% Habitat

= 0.4 SR SR SR o0(>-c 03-0"0":0. 0 03

0.2 _

0.2

= 04 0.0 H= 0.0 H= 0.05 -H=

? " 0.2 0

= 03 I

0 4. - 0.3 i0 0 00:.y: 0 0. O o- . -- . .4 -• 80ro.-4.-.-.-.*:- . o 0::. . : : 0: j•_ 0:- 0.3 - 04 H=01-0 H=01 0 H=0.5 0 S0.4 00 H=1.0? H=10? i i H=1.? _ 0.1 02 O ?t

04S0.1 - ,0w0 Owa 0 o 000 •o.2-0(b) Real landscapes ( 1 O Iowa 2 Iowa 3 O O 0.4 OIowaPatch si Patch • "••~.•o 0 o 0i0 .• o.•[ o •? oo ~oo0O' P0. t s c[: ,, P s .?,, Patch size oo*?; ;..••..•• ?:~(~~)?......

Patch size Patch size Patch size

Fig. 4. The predictedpatch-level frequency of occurrence(mean individuals/cell, ? SE) of malebobolinks for threemodels as a functionof patchsize, the amountof habitatand degreeof fragmentationin (a) theoreticallandscapes and (b) reallandscapes. Null modelsused interiorestimates, nearest-distance models used only the nearestdistance from edges in predictingoccurrence (based on single edge and interiorestimates), whereas next-nearest-distance models used both the nearestand next-nearest distancein predictingoccurrence (based on single-edge,double-edge, and interiorestimates). H denotes the relativespatial contagion,or fragmentation,of fractallandscapes (with H= being less clumped,or more fragmented,and H = 1-0being 0.0 more clumped,or less fragmented),while SR denotessimple random landscapes. For real landscapes,numbers refer to maps shownin Fig. 2. Standarderrors were estimated across landscape replicates; therefore, no standarderrors were calculated for each real landscape.

Iowa grasslands (Fletcher 2003; Fletcher & Koford composition, which was related directly to the propor- 2003a). Clearly, a mechanistic approach to multiple tion of habitat located near multiple edges. This edge effects will improve predictability and the ability and other recent modelling attempts (Malcolm 2001) to link edge avoidance with fitness, which is needed to suggest that multiple edges are probably influencing understand the demographic consequences for species large-scale processes primarily in highly fragmented in fragmented landscapes. landscapes. The second pattern that emerged was that models incorporating edge effects predicted much lower fre- MODELS OF EDGE EFFECTS IN FRAGMENTED quencies of occurrence in small patches than models LANDSCAPES that did not assume an edge effect. This was not sur- When extrapolating edge effects to fragmented land- prising. What was surprising was the extent that this ? 2005 British scapes, two primary patterns emerged. First, models effect emerged, in which frequencies of occurrence only EcologicalSociety, Journal of Animal incorporating multiple edge effects tended to predict converged on null model predictions in very large Ecology, 74, lower landscape-level frequencies of occurrence in only patches (> 150 ha). Bobolinks have been reported to be 342-352 the most fragmentedlandscapes, regardless of landscape area sensitive throughout much of their range (Herkert 350 1994; & Jelinski 1999; Johnson & Igl 2001), O Null Helzer R. J Fletcher being less likely to occur in relatively small patches, in distance SNearest the order of 30-60 ha (Herkert 1994; Helzer & Jelinski SNext-nearest distance 1999). The models developed here suggest that observed (a) Theoreticallandscapes edge effects occurring within approximately 90-120 m from edges can potentially explain higher occurrence 10% Habitat probabilities and densities in large patches within fragmented landscapes. Although processes of edge avoidance might operate distinctly from processes of area 0-43 0.3 - sensitivity (Villard 1998), edge effects could none the less be a primary mechanism explaining patch-size effects (Bender, Contreras & Fahrig 1998; Johnson & Igl 2001; but see Bollinger & Switzer 2002). Indeed, Helzer & Jelinski (1999) found that perimeter-area ratios, which 0.0'- - 4- reflect the relative proportion of edge within patches, were better at predicting bobolink occurrence than 0.4 30% Habitat patch size. A recent meta-analysis of patch-size effects also found that species avoiding edges exhibited increased densities in larger patches, whereas species .o 0-20.:3 - preferring edges exhibited the opposite pattern (Bender

U- et al. 1998). My modelling approach allowed for insight into 0.2- -1 some potential large-scale implications of edge effects, 0.4 yet it was not intended to estimate real distributions in fragmented landscapes. Many issues arise when extrap- local to 0o0 olating patterns heterogeneous landscapes 50% Habitat (Wiens et al. 1993; Ries et al. 2004), and neutral land- -0- scapes are not intended to mimic real landscapes but "o?1 4 -- O- -- -- instead provide an objective approach for investigating 0-3 different landscape conditions that vary independently 0.0 in the amount of habitat and degree of fragmentation "o• 0.2 0-2 (With & King 1997). To address implications of multi- Fragmentationt ple edge effects, I modelled only effects arising from two edges within patches, because bobolink data were limited to information on two edges. While the distances to the two nearest edges captured most variation in a~ 0?30.3 H= 1-0 H= 0-5 H= 0?0 SR edge configurations, particularly in the real, highly Fragmentation C fragmented Iowa landscapes (Table 2), edge effects could be stronger in extremely fragmented landscapes '-o (b) Real landscapes if more than two edges are incorporated into the o0.1 - modelling process. 0.4 0.~O00 O Two other approaches have been used for modelling 0-0 - multiple edge effects. Mancke & Gavin (2000) developed 0.3 1 owa 2 owa H=owa H= H= 3SR an edge 'depth' index that incorporated distances to S0.2 four edges within patches, yet that approach does not isolate contributions of multiple edges within patches. Malcolm (1994), and subsequent extensions by --- 0.1 Fernuindezet al. (2002) modelled multiple edge effects by considering the edge as a collection of points and 0.0 ' ' the effect. This effect Iowa 1 lowa 2 lowa 3 isolating 'point' edge point edge

Fig. 5. The predictedlandscape-level frequency of occur- (basedon single-edge,double-edge, and interiorestimates). rence(mean individuals/cell, + SE) of malebobolinks for three H denotes the relativespatial contagion, or fragmentation, models as a function of the amount of habitat and degree of fractal (with H = less or landscapes 0.0 being clumped, of fragmentationin (a) theoreticallandscapes and (b) real more fragmented, and H = being more clumped, or 1.0 ? 2005 British landscapes.Null models used interior estimates, nearest- less fragmented),while SR denotes simple random land- EcologicalSociety, distancemodels used only the nearestdistance from edges scapes.For reallandscapes, numbers refer to mapsshown in Journalof Animal in predictingoccurrence (based on single edge and interior Fig. 2. Standard errors were estimated across landscape Ecology,74, estimates),whereas next-nearest-distance models used both replicates;therefore, no standarderrors were calculatedfor 342-352 the nearestand next-nearestdistance in predictingoccurrence eachreal landscape. 351 can then be integrated across the entire region of influ- Bender,D.J., Contreras, T.A. & Fahrig,L. (1998)Habitat loss Multipleedge ence to estimate the 'total' edge effect (Malcolm 1994, and populationdecline: a meta-analysisof the patchsize effect. Ecology, 79, 517-533. effects 2001; Fernindez et al. 2002). While that approach is Bollinger,E.K. & Gavin,T.A. (1989) The effects of sitequality robust to boundaries complex and allows for extra- on breeding-sitefidelity in bobolinks.Auk, 106, 584-594. polating single edge effects across all edges in a patch, in Bollinger,E.K. & Switzer,P.V. (2002) Modeling the impact of practice point edge effects can rarely,if ever, be empir- edgeavoidance on aviannest densities in habitatfragments. 1567-1575. ically isolated and measured (FerniAndezet al. 2002), EcologicalApplications, 12, Brand,L.A. & George,T.L. (2001) of because observed effects are confounded by all nearby Response passerine birdsto forestedge in coastredwood forest fragments. Auk, edge segments within a patch. Although the approach 118, 678-686. I used does not account for complex boundaries, it Burnham,K.P. & Anderson,D.R. (1998)Model Selection and provides a practical and straightforward approach to Inference:a Practical Information-TheoreticApproach. isolate effects from multiple edges and allows for other Springer-Verlag,New York. Cadenasso,M.L. & Pickett, S.T.A. (2001) Effect of struc- covariates to be included in the modelling process. edge tureon theflux of speciesinto forest interiors. Conservation Biology, 15, 91-98. Conclusions Camp,M. & Best, L.B. (1993) Birdabundance and species richnessin roadsidesadjacent to Iowarowcrop fields. Wild- Ultimately, incorporating multiple edges into a general life Society Bulletin, 21, 315-325. Chen,J., Franklin, & Spies,T.A. (1995) framework on edge effects will help determine if edge J.FE Growing-season microclimaticgradients from clearcut edges into old-growth effects on scales operate relativelylarge (Laurance2000; Douglas-fir forests. Ecological Applications, 5, 74-86. Ries et al. 2004). In addition, conservation strategies FernAndez,C., Acosta,J.E, Abelli, G., L6pez,E & Diaz, M. that use edge responses in assessing impacts of habitat (2002)Complex edge effectfields as additiveprocesses in change (e.g. Sisk et al. 2002) could be refined by incor- patchesof ecologicalsystems. Ecological Modelling, 149, 273-283. porating multiple edges into models (Malcolm 2001). Fletcher,R.J. Jr (2003)Spatial and temporalscales of distri- As size decreases and patch fragmentation increases, bution and demographyin breeding songbirds: implications ignoring issues of multipleedges becomes of paramount of habitatfragmentation and restoration. PhD thesis, Iowa concern (see also Malcolm 2001). Multiple edges are StateUniversity. also likely to be of critical importance for species that Fletcher,R.J. Jr & Koford,R.R. (2002)Habitat and landscape associationsof birdsin restoredand use narrow linear habitats, such as conservation corri- breeding nativegrass- lands.Journal of WildlifeManagement, 66, 1011-1022. dors Haddad & Baum when (e.g. 1999). Furthermore, Fletcher,R.J. Jr & Koford,R.R. (2003a)Spatial responses of different types of edges converge, multiple edge effects bobolinks (Dolichonyx oryzivorus) near different types of could be complex based on the relative influence of edgesin northernIowa. Auk, 120, 799-810. each edge type (FernAndezet al. 2002). As we continue Fletcher,R.J. Jr & Koford,R.R. (2003b)Changes in breeding birdpopulations with habitat restoration in northernIowa. to develop our understandingof habitat fragmentation, American Midland Naturalist, 150, 83-94. will be valuableto determinethe of it generality multiple Gardner,R.H. (1999) RULE:map generationand a spatial edge effects on other processes and their potential analysis program. Landscape Ecological Analysis: Issues contributions to the widespread patch-size effects and Applications(eds J.M. Klopatek& R.H. Gardner), observed in fragmented landscapes. pp. 280-303. Springer-Verlag,New York. Haddad,N.M. & Baum,K.A. (1999)An experimentaltest of corridoreffects on butterflydensities. Ecological Applications, Acknowledgements 9, 623-633. Harper,K.A. & MacDonald,S.E. (2001) Structure and com- I am indebted to Rolf Koford for his continued advice positionof riparianboreal forest: new methods for analyzing and support throughout all phases of this investigation. edgeinfluence. Ecology, 82, 649-659. The US Fish and Wildlife Service, Iowa Department Harrison,S. & Bruna,E. (1999)Habitat fragmentation and large-scaleconservation: what do we knowfor sure? of Natural Resourcesand USGS-BRD Ecog- providedsupport raphy,22, 225-232. for this research.S. M. Nusser and P. M. Dixon provided Helzer,C.J. & Jelinski,D.E. (1999) The relative importance of helpful statistical advice. K. A. Moloney helped re- patcharea and perimeter-arearatio to grasslandbreeding solve a bug in the simulation model. This study could birds. Ecological Applications, 9, 1448-1458. not have been completed without the invaluable help Herkert,J.R. (1994)The effectsof habitatfragmentation on Midwestern grassland bird communities. Ecological of many field assistants, especially J.Fekete, J. McEntee, Applications, 4, 461-471. C. Wisniewski and D. Williams. A. D. W R. Chalfoun, Johnson,D.H. & Igl, L.D.(2001) Area requirements of grass- Clark,B. J.Danielson, R. R. Koford,J. L. Orrock,L. Ries, land birds:a regionalperspective. Auk, 118, 24-34. J. R. Sauer and two anonymous reviewers provided Johnson,R.G. & Temple,S.A. (1990) Nest predationand valuablecomments on earlierversions of this manuscript. brood parasitism of tallgrass prairie birds. Journalof WildlifeManagement, 54, 106-111. Keitt,T.H., Bjornstad, O.N., Dixon, P.M. & Citron-Pousty,S. O 2005 British References (2002) Accounting for spatial pattern when modeling organism-environmentinteractions. Ecography, 25, 616- EcologicalSociety, Bakker,K.K., Naugle,D.E. & Higgins,K.E (2002)Incorpo- 625. Journal of Animal rating landscape attributes into models for migratory Kuehl,A.K. & Clark,W.R. (2002) Predator activity related to 74, Ecology, grassland bird conservation. Conservation Biology, 16, landscapefeatures in northernIowa. Journal 342-352 of Wildlife 1638-1646. Management, 66, 1224-1234. 352 Laurance,W.E (2000) Do edgeeffects occur over large spatial breeding bird survey, 1966-96. Studies in AvianBiology, 19, 27-44. R. J Fletcher scales? Trendsin Ecology and Evolution, 15, 134-135. Laurance,W.E, Ferreira,L.V., Rankin-de Merona, J.M. & Ries, L., Fletcher,R.J. Jr, Battin,J. & Sisk,T.D. (2004)Eco- Laurance,S.G. (1998) Rain forestfragmentation and the logicalresponses to habitatedges: mechanisms, models, and dynamicsof Amazoniantree communities.Ecology, 79, variability explained. Annual Review of Ecology, Evolution, 2032-2040. and Systematics, 35, 491-522. Laurance,W.E & Yensen,E. (1991)Predicting the impactsof SAS Institute(2001) User'sGuide, version 8. SAS Institute, edge effectsin fragmentedhabitats. Biological Conserva- Carey. tion,55, 77-92. Sisk,T.D., Haddad, N.M. & Ehrlich,P.R. (1997) Bird assem- Littell,R.C., Milliken, G.A., Stroup,W.W & Wolfinger,R.D. blagesin patchywoodlands: modeling the effectsof edge (1996) SAS System for Mixed Models. SAS Institute Inc., and matrix habitats. Ecological Applications, 7, 1170- Cary,North Carolina. 1180. Malcolm, J.R. (1994) Edge effects in central Amazonian Sisk,T.D., Noon, B.R.& Hampton,H.M. (2002)Estimating forestfragments. Ecology, 75, 2438-2445. the effectivearea of habitatpatches in heterogeneousland- Malcolm,J.R. (1998) A modelof conductiveheat flow in for- scapes. Predicting Species Occurrences:Issues of Accuracy est edgesand fragmentedlandscapes. Climatic Change, 39, andScale (eds J.M. Scott, P.J. Heglund & M.L. Morrison), 487-502. pp. 713-725. IslandPress, Washington, DC. Malcolm, J.R. (2001) Extending models of edge effects Villard,M.A. (1998)On forest-interiorspecies, edge avoid- to diverselandscape configurations, with a test from the ance, area sensitivity,and dogmasin avianconservation. Neotropics. 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? 2005 British EcologicalSociety, Journal of Animal Ecology, 74, 342-352